Reactive power optimisation of distribution network with distributed generation based on genetic and immune algorithm

With the rapid development of new energy technologies, distributed power generation technology has attracted widely attention. The advantages of them are small investment, clean and environmental protection, reliable, and flexible power supply. They can output (or absorb) continuously adjustable reactive power and participate in the reactive power optimisation, which can keep the balance of reactive power and optimise the distribution of reactive power flow. In this study, firstly, the power flow model of typical distributed power supplies: wind power, solar power, and gas turbine power generation are researched. Then, the distributed power supply as a continuously adjustable reactive power device, combined with the traditional equipment, participate in reactive power optimisation. An objective function considering system loss is proposed to find optimal solution. Finally, the IEEE33 node system is used for verification. Results show that the distributed power supply can effectively reduce the system loss and improve the voltage stability. Meanwhile, the effectiveness and feasibility of the improved algorithm are verified. The optimisation of this study is the combination of genetic algorithm and immune algorithm. It can make up for the lack of local optimisation ability of genetic algorithm. Compared with the single algorithm, the global optimisation ability is greatly enhanced.